Q-omics provides the consensus-scored SMO profile across patient tissues and cancer cell-line models. SMO expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, SMO is differentially expressed in 10, with the highest sampling consensus in KICH. Additionally, SMO RNA expression shows 19,090 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight ACC, KICH, and TGCT as cancer lineages where SMO shows reproducible signals across survival, tumor–normal expression, and patient cross-omics analyses.
Every result is evaluated using two consensus scores. Sampling consensus measures how consistently a finding is reproduced within a cancer lineage across different conditions. Lineage consensus measures how broadly the result is shared across cancer types, distinguishing pan-cancer signals from lineage-specific patterns.
Premium analyses for SMO — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SMO survival associations across molecular data types. SMO RNA expression shows survival associations in the most cancer types (21), followed by mutation status (8) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SMO RNA expression–survival associations across cancer types. High SMO expression shows unfavorable associations in ACC, LGG, MESO, STAD and BLCA, but favorable associations in OV. The ACC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify ACC as the clearest survival context for SMO RNA expression.
This table summarizes SMO tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 6. The strongest signals are observed in KICH for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for SMO. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SMO shows lower tumor expression in KICH and BRCA and higher tumor expression in LUSC, LIHC, LUAD and KIRP. The KICH box plot shows higher SMO RNA expression in normal versus tumor tissue (log2 FC = −2.160, t-test p < 0.001).
This table shows molecular features associated with SMO in patient tissues and cancer cell lines. In patient samples, SMO shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, SMO RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in SKIN and BLOOD_Leukemia.
